D. Fearon

The paper evaluates how many crystal structures are needed for accurate pose prediction in drug discovery, finding that five structures per scaffold often suffice.

The paper identifies fragment binders and mutationally intolerant sites in Zika virus NS2B-NS3 protease to develop resistance-resilient antiviral inhibitors.

The paper solves the crystal structure of Arabidopsis thaliana FatA and identifies fragments that target novel regions, enabling the design of new herbicides with improved potency and novel interaction modes.

This study identifies multiple binding sites on the dengue virus polymerase through crystallographic fragment screening, providing insights for developing non-nucleoside antiflavivirals.

This paper introduces a computational pipeline for identifying broad-spectrum antivirals by analyzing viral sequences, predicting ligand poses, and scoring protein-ligand complexes, validated on SARS-CoV-2 and MERS-CoV datasets.

The paper identifies orally bioavailable inhibitors of the Zika virus NS2B-NS3 protease that show antiviral activity in vitro and reduce viral RNA load in a murine infection model.

This paper combines crystallographic fragment screening, algorithmic merging, and automated synthesis to generate scaffolds targeting NCS-1 PPIs involved in neurological disorders.

This paper describes the optimization of a SARS-CoV-2 Mpro inhibitor to address genotoxic and metabolic liabilities, leading to improved in vivo efficacy and exposure.

The paper identifies chemical fragments targeting the Chikungunya virus nsP3 macrodomain through crystallographic screening, revealing novel binding sites and potential inhibitors.

The paper identifies potent nsp3-mac1 inhibitors but finds they do not translate to antiviral activity in cell culture models.

This study identifies fragments binding to EV-D68 3C protease through crystallography and expands them into lead-like compounds, revealing novel binding modes and structural insights for drug design.

The paper identifies 75 fragments that bind to Coxsackievirus A16 2A protease, including 38 unique compounds in the active site, offering a path for broad-spectrum anti-enteroviral inhibitors.

This study uses high-throughput crystallographic fragment screening to identify 46 fragment binding poses on ZIKV NS3Hel, providing templates for antiviral drug design.

The paper evaluates the druggability of LC3/GABARAP for autophagy modulators and identifies ligands that bind to the HP2 pocket of the LIR docking site.

This study characterizes SARS-CoV-2 NSP15 endoribonuclease, identifies its allosteric properties, and discovers new allosteric sites for inhibitor development.

The paper computationally designs and experimentally validates potent inhibitors of the SARS-CoV-2 Nsp3 Macrodomain, identifying 160 ligands and 152 crystal structures with submicromolar affinity.

The paper introduces a computational pipeline to design irreversible inhibitors, identifying a potent SARS-CoV-2 Mpro inhibitor with low micromolar IC50.

This paper develops a machine learning framework to predict protein-ligand affinity from structural data, enabling the design of potent inhibitors against SARS-CoV-2 Main Protease.

This study presents crystal structures of SARS-CoV-2 NSP13 and identifies druggable pockets, revealing potential targets for antiviral drug development through fragment screening.

The paper identifies new chemical fragments binding to the SARS-CoV-2 Nsp3 macrodomain through crystallographic screening and computational docking, validating their binding with biophysical techniques.

The paper describes an open-science drug discovery campaign that identified a non-covalent, non-peptidic inhibitor of SARS-CoV-2 main protease using crowdsourcing and computational methods.

The paper identifies fragment hits against SARS-CoV-2 main protease using crystallography and mass spectrometry, revealing structural insights for drug design.